Pandas Profiling Report

Dataset statistics

Number of variables	49
Number of observations	347469
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	129.9 MiB
Average record size in memory	392.0 B

Variable types

Numeric	10
Categorical	39

Alerts

`geo_level_1_id` is highly correlated with `geo_level_2_id` and 1 other fields	High correlation
`geo_level_2_id` is highly correlated with `geo_level_1_id` and 1 other fields	High correlation
`geo_level_3_id` is highly correlated with `geo_level_1_id` and 1 other fields	High correlation
`count_floors_pre_eq` is highly correlated with `height_percentage` and 1 other fields	High correlation
`height_percentage` is highly correlated with `count_floors_pre_eq` and 1 other fields	High correlation
`land_surface_condition_1` is highly correlated with `land_surface_condition_3`	High correlation
`land_surface_condition_3` is highly correlated with `land_surface_condition_1`	High correlation
`foundation_type` is highly correlated with `roof_type_3` and 1 other fields	High correlation
`roof_type_1` is highly correlated with `roof_type_2`	High correlation
`roof_type_2` is highly correlated with `roof_type_1`	High correlation
`roof_type_3` is highly correlated with `foundation_type` and 2 other fields	High correlation
`ground_floor_type` is highly correlated with `roof_type_3`	High correlation
`other_floor_type_1` is highly correlated with `other_floor_type_2` and 1 other fields	High correlation
`other_floor_type_2` is highly correlated with `other_floor_type_1`	High correlation
`other_floor_type_3` is highly correlated with `count_floors_pre_eq` and 2 other fields	High correlation
`other_floor_type_4` is highly correlated with `roof_type_3`	High correlation
`position_1` is highly correlated with `position_2`	High correlation
`position_2` is highly correlated with `position_1`	High correlation
`has_superstructure_mud_mortar_stone` is highly correlated with `foundation_type`	High correlation
`has_secondary_use` is highly correlated with `has_secondary_use_agriculture` and 1 other fields	High correlation
`has_secondary_use_agriculture` is highly correlated with `has_secondary_use`	High correlation
`has_secondary_use_hotel` is highly correlated with `has_secondary_use`	High correlation
`geo_level_1_id` is highly correlated with `geo_level_2_id` and 1 other fields	High correlation
`geo_level_2_id` is highly correlated with `geo_level_1_id` and 1 other fields	High correlation
`geo_level_3_id` is highly correlated with `geo_level_1_id` and 1 other fields	High correlation
`count_floors_pre_eq` is highly correlated with `height_percentage` and 1 other fields	High correlation
`height_percentage` is highly correlated with `count_floors_pre_eq` and 1 other fields	High correlation
`land_surface_condition_1` is highly correlated with `land_surface_condition_3`	High correlation
`land_surface_condition_3` is highly correlated with `land_surface_condition_1`	High correlation
`foundation_type` is highly correlated with `roof_type_3` and 3 other fields	High correlation
`roof_type_1` is highly correlated with `roof_type_2`	High correlation
`roof_type_2` is highly correlated with `roof_type_1`	High correlation
`roof_type_3` is highly correlated with `foundation_type` and 2 other fields	High correlation
`ground_floor_type` is highly correlated with `foundation_type` and 3 other fields	High correlation
`other_floor_type_1` is highly correlated with `other_floor_type_2` and 1 other fields	High correlation
`other_floor_type_2` is highly correlated with `other_floor_type_1`	High correlation
`other_floor_type_3` is highly correlated with `count_floors_pre_eq` and 2 other fields	High correlation
`other_floor_type_4` is highly correlated with `foundation_type` and 2 other fields	High correlation
`position_1` is highly correlated with `position_2`	High correlation
`position_2` is highly correlated with `position_1`	High correlation
`has_superstructure_mud_mortar_stone` is highly correlated with `foundation_type`	High correlation
`has_superstructure_cement_mortar_brick` is highly correlated with `ground_floor_type`	High correlation
`has_secondary_use` is highly correlated with `has_secondary_use_agriculture` and 1 other fields	High correlation
`has_secondary_use_agriculture` is highly correlated with `has_secondary_use`	High correlation
`has_secondary_use_hotel` is highly correlated with `has_secondary_use`	High correlation
`geo_level_1_id` is highly correlated with `geo_level_2_id` and 1 other fields	High correlation
`geo_level_2_id` is highly correlated with `geo_level_1_id` and 1 other fields	High correlation
`geo_level_3_id` is highly correlated with `geo_level_1_id` and 1 other fields	High correlation
`count_floors_pre_eq` is highly correlated with `height_percentage` and 1 other fields	High correlation
`height_percentage` is highly correlated with `count_floors_pre_eq` and 1 other fields	High correlation
`land_surface_condition_1` is highly correlated with `land_surface_condition_3`	High correlation
`land_surface_condition_3` is highly correlated with `land_surface_condition_1`	High correlation
`foundation_type` is highly correlated with `roof_type_3` and 1 other fields	High correlation
`roof_type_1` is highly correlated with `roof_type_2`	High correlation
`roof_type_2` is highly correlated with `roof_type_1`	High correlation
`roof_type_3` is highly correlated with `foundation_type` and 2 other fields	High correlation
`ground_floor_type` is highly correlated with `roof_type_3`	High correlation
`other_floor_type_1` is highly correlated with `other_floor_type_2` and 1 other fields	High correlation
`other_floor_type_2` is highly correlated with `other_floor_type_1`	High correlation
`other_floor_type_3` is highly correlated with `count_floors_pre_eq` and 2 other fields	High correlation
`other_floor_type_4` is highly correlated with `roof_type_3`	High correlation
`position_1` is highly correlated with `position_2`	High correlation
`position_2` is highly correlated with `position_1`	High correlation
`has_superstructure_mud_mortar_stone` is highly correlated with `foundation_type`	High correlation
`has_secondary_use` is highly correlated with `has_secondary_use_agriculture` and 1 other fields	High correlation
`has_secondary_use_agriculture` is highly correlated with `has_secondary_use`	High correlation
`has_secondary_use_hotel` is highly correlated with `has_secondary_use`	High correlation
`has_secondary_use` is highly correlated with `has_secondary_use_hotel` and 1 other fields	High correlation
`other_floor_type_4` is highly correlated with `ground_floor_type` and 2 other fields	High correlation
`ground_floor_type` is highly correlated with `other_floor_type_4` and 2 other fields	High correlation
`position_1` is highly correlated with `position_2`	High correlation
`has_superstructure_rc_engineered` is highly correlated with `foundation_type`	High correlation
`roof_type_1` is highly correlated with `roof_type_2`	High correlation
`has_superstructure_cement_mortar_brick` is highly correlated with `ground_floor_type` and 1 other fields	High correlation
`other_floor_type_2` is highly correlated with `other_floor_type_1`	High correlation
`foundation_type` is highly correlated with `other_floor_type_4` and 5 other fields	High correlation
`has_secondary_use_hotel` is highly correlated with `has_secondary_use`	High correlation
`roof_type_3` is highly correlated with `other_floor_type_4` and 2 other fields	High correlation
`other_floor_type_1` is highly correlated with `other_floor_type_2` and 1 other fields	High correlation
`has_superstructure_rc_non_engineered` is highly correlated with `foundation_type`	High correlation
`roof_type_2` is highly correlated with `roof_type_1`	High correlation
`land_surface_condition_1` is highly correlated with `land_surface_condition_3`	High correlation
`has_secondary_use_agriculture` is highly correlated with `has_secondary_use`	High correlation
`has_superstructure_mud_mortar_stone` is highly correlated with `foundation_type`	High correlation
`position_2` is highly correlated with `position_1`	High correlation
`land_surface_condition_3` is highly correlated with `land_surface_condition_1`	High correlation
`other_floor_type_3` is highly correlated with `other_floor_type_1`	High correlation
`geo_level_1_id` is highly correlated with `geo_level_2_id` and 1 other fields	High correlation
`geo_level_2_id` is highly correlated with `geo_level_1_id` and 1 other fields	High correlation
`geo_level_3_id` is highly correlated with `geo_level_1_id` and 1 other fields	High correlation
`count_floors_pre_eq` is highly correlated with `height_percentage` and 2 other fields	High correlation
`height_percentage` is highly correlated with `count_floors_pre_eq` and 1 other fields	High correlation
`land_surface_condition_1` is highly correlated with `land_surface_condition_2` and 1 other fields	High correlation
`land_surface_condition_2` is highly correlated with `land_surface_condition_1`	High correlation
`land_surface_condition_3` is highly correlated with `land_surface_condition_1`	High correlation
`foundation_type` is highly correlated with `roof_type_3` and 2 other fields	High correlation
`roof_type_1` is highly correlated with `roof_type_2` and 1 other fields	High correlation
`roof_type_2` is highly correlated with `roof_type_1`	High correlation
`roof_type_3` is highly correlated with `foundation_type` and 7 other fields	High correlation
`ground_floor_type` is highly correlated with `foundation_type` and 1 other fields	High correlation
`other_floor_type_1` is highly correlated with `count_floors_pre_eq` and 2 other fields	High correlation
`other_floor_type_2` is highly correlated with `other_floor_type_1`	High correlation
`other_floor_type_3` is highly correlated with `count_floors_pre_eq` and 2 other fields	High correlation
`other_floor_type_4` is highly correlated with `foundation_type` and 5 other fields	High correlation
`position_1` is highly correlated with `position_2`	High correlation
`position_2` is highly correlated with `position_1` and 1 other fields	High correlation
`position_3` is highly correlated with `position_2`	High correlation
`has_superstructure_mud_mortar_stone` is highly correlated with `roof_type_3` and 3 other fields	High correlation
`has_superstructure_mud_mortar_brick` is highly correlated with `has_superstructure_mud_mortar_stone`	High correlation
`has_superstructure_cement_mortar_brick` is highly correlated with `roof_type_3` and 2 other fields	High correlation
`has_superstructure_timber` is highly correlated with `has_superstructure_bamboo`	High correlation
`has_superstructure_bamboo` is highly correlated with `has_superstructure_timber`	High correlation
`has_superstructure_rc_non_engineered` is highly correlated with `roof_type_3` and 1 other fields	High correlation
`has_superstructure_rc_engineered` is highly correlated with `roof_type_3` and 1 other fields	High correlation
`has_secondary_use` is highly correlated with `has_secondary_use_agriculture` and 1 other fields	High correlation
`has_secondary_use_agriculture` is highly correlated with `has_secondary_use`	High correlation
`has_secondary_use_hotel` is highly correlated with `has_secondary_use`	High correlation
`building_id` has unique values	Unique
`age` has 34725 (10.0%) zeros	Zeros
`count_families` has 27937 (8.0%) zeros	Zeros

Reproduction

Analysis started	2022-04-30 11:02:59.782335
Analysis finished	2022-04-30 11:05:40.165238
Duration	2 minutes and 40.38 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

building_id
Real number (ℝ_≥0)

UNIQUE

Distinct	347469
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	525913.5838

Minimum	4
Maximum	1052934
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.7 MiB

Quantile statistics

Minimum	4
5-th percentile	52200.8
Q1	261999
median	526071
Q3	789588
95-th percentile	1000694
Maximum	1052934
Range	1052930
Interquartile range (IQR)	527589

Descriptive statistics

Standard deviation	304354.4791
Coefficient of variation (CV)	0.5787157595
Kurtosis	-1.201737909
Mean	525913.5838
Median Absolute Deviation (MAD)	263777
Skewness	0.001061379559
Sum	1.827386671 × 10¹¹
Variance	9.263164894 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
802906	1	< 0.1%
48839	1	< 0.1%
846160	1	< 0.1%
603042	1	< 0.1%
278056	1	< 0.1%
557238	1	< 0.1%
233008	1	< 0.1%
751316	1	< 0.1%
679265	1	< 0.1%
463952	1	< 0.1%
Other values (347459)	347459	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
4	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
12	1	< 0.1%
13	1	< 0.1%
16	1	< 0.1%
17	1	< 0.1%
25	1	< 0.1%
28	1	< 0.1%
31	1	< 0.1%

Value	Count	Frequency (%)
1052934	1	< 0.1%
1052931	1	< 0.1%
1052929	1	< 0.1%
1052926	1	< 0.1%
1052923	1	< 0.1%
1052921	1	< 0.1%
1052915	1	< 0.1%
1052911	1	< 0.1%
1052909	1	< 0.1%
1052908	1	< 0.1%

geo_level_1_id
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	31
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.239031638

Minimum	1.73088658
Maximum	2.794480356
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.7 MiB

Quantile statistics

Minimum	1.73088658
5-th percentile	1.73088658
Q1	2.026023244
median	2.171745152
Q3	2.44645707
95-th percentile	2.794480356
Maximum	2.794480356
Range	1.063593776
Interquartile range (IQR)	0.4204338258

Descriptive statistics

Standard deviation	0.2875388683
Coefficient of variation (CV)	0.1284210832
Kurtosis	-0.5526004862
Mean	2.239031638
Median Absolute Deviation (MAD)	0.1707854595
Skewness	0.1379842714
Sum	777994.0841
Variance	0.08267860079
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=31)

Value	Count	Frequency (%)
2.161724294	32485	9.3%
1.73088658	30002	8.6%
2.341953893	29399	8.5%
2.794480356	29265	8.4%
2.297725598	25565	7.4%
2.485272537	25465	7.3%
1.926463755	22761	6.6%
2.56336893	19944	5.7%
2.162136189	19462	5.6%
2.44645707	16786	4.8%
Other values (21)	96335	27.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1.73088658	30002	8.6%
1.894656489	1737	0.5%
1.919702602	3579	1.0%
1.926463755	22761	6.6%
1.93765612	12846	3.7%
1.960755276	3588	1.0%
2.000959693	8358	2.4%
2.020476545	3595	1.0%
2.026023244	5213	1.5%
2.049591599	2319	0.7%

Value	Count	Frequency (%)
2.794480356	29265	8.4%
2.708372531	4200	1.2%
2.56336893	19944	5.7%
2.485272537	25465	7.3%
2.44645707	16786	4.8%
2.40754717	349	0.1%
2.341953893	29399	8.5%
2.337712895	10895	3.1%
2.331564987	9995	2.9%
2.297725598	25565	7.4%

geo_level_2_id
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	1024
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.238639886

Minimum	1
Maximum	3
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.7 MiB

Quantile statistics

Minimum	1
5-th percentile	1.630630631
Q1	2.017964072
median	2.210382514
Q3	2.47983871
95-th percentile	2.877300613
Maximum	3
Range	2
Interquartile range (IQR)	0.4618746378

Descriptive statistics

Standard deviation	0.3579539089
Coefficient of variation (CV)	0.1598979412
Kurtosis	-0.3556521627
Mean	2.238639886
Median Absolute Deviation (MAD)	0.2237753708
Skewness	0.02249890571
Sum	777857.9624
Variance	0.1281310009
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1.532194156	5367	1.5%
1.895238095	3317	1.0%
2.285576923	2805	0.8%
2.218627451	2675	0.8%
1.939377965	2548	0.7%
2.51875	2343	0.7%
2.182183908	2310	0.7%
1.836267606	2249	0.6%
2.540973872	2217	0.6%
2.265682657	2129	0.6%
Other values (1014)	319509	92.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	8	< 0.1%
1.218181818	157	< 0.1%
1.226415094	76	< 0.1%
1.231481481	148	< 0.1%
1.25	20	< 0.1%
1.282868526	355	0.1%
1.304347826	34	< 0.1%
1.325	105	< 0.1%
1.333333333	3	< 0.1%
1.35483871	234	0.1%

Value	Count	Frequency (%)
3	62	< 0.1%
2.990291262	282	0.1%
2.984771574	254	0.1%
2.977443609	177	0.1%
2.97706422	275	0.1%
2.976878613	457	0.1%
2.965384615	338	0.1%
2.958525346	289	0.1%
2.953907816	651	0.2%
2.951612903	256	0.1%

geo_level_3_id
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	1634
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.238719798

Minimum	1
Maximum	3
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.7 MiB

Quantile statistics

Minimum	1
5-th percentile	1.557446809
Q1	2
median	2.2
Q3	2.5
95-th percentile	2.944444444
Maximum	3
Range	2
Interquartile range (IQR)	0.5

Descriptive statistics

Standard deviation	0.3992658962
Coefficient of variation (CV)	0.1783456316
Kurtosis	-0.1751926784
Mean	2.238719798
Median Absolute Deviation (MAD)	0.2310344828
Skewness	-0.0501692177
Sum	777885.7295
Variance	0.1594132559
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2	21349	6.1%
3	9985	2.9%
2.5	3989	1.1%
2.333333333	3264	0.9%
2.25	2966	0.9%
2.2	2851	0.8%
2.166666667	2850	0.8%
2.142857143	2620	0.8%
2.125	2530	0.7%
2.666666667	1892	0.5%
Other values (1624)	293173	84.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	366	0.1%
1.034482759	37	< 0.1%
1.037037037	41	< 0.1%
1.041666667	37	< 0.1%
1.043478261	30	< 0.1%
1.055555556	26	< 0.1%
1.066666667	24	< 0.1%
1.071428571	56	< 0.1%
1.074074074	41	< 0.1%
1.083333333	21	< 0.1%

Value	Count	Frequency (%)
3	9985	2.9%
2.989795918	120	< 0.1%
2.986111111	92	< 0.1%
2.985714286	89	< 0.1%
2.984848485	82	< 0.1%
2.983870968	76	< 0.1%
2.982905983	147	< 0.1%
2.981818182	75	< 0.1%
2.981481481	146	< 0.1%
2.979591837	60	< 0.1%

count_floors_pre_eq
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	9
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.130578555

Minimum	1
Maximum	9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.7 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	2
Q3	2
95-th percentile	3
Maximum	9
Range	8
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.72776061
Coefficient of variation (CV)	0.3415788675
Kurtosis	2.36001261
Mean	2.130578555
Median Absolute Deviation (MAD)	0
Skewness	0.8418180575
Sum	740310
Variance	0.5296355054
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
2	209029	60.2%
3	74171	21.3%
1	53705	15.5%
4	7186	2.1%
5	3039	0.9%
6	283	0.1%
7	52	< 0.1%
8	3	< 0.1%
9	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	53705	15.5%
2	209029	60.2%
3	74171	21.3%
4	7186	2.1%
5	3039	0.9%
6	283	0.1%
7	52	< 0.1%
8	3	< 0.1%
9	1	< 0.1%

Value	Count	Frequency (%)
9	1	< 0.1%
8	3	< 0.1%
7	52	< 0.1%
6	283	0.1%
5	3039	0.9%
4	7186	2.1%
3	74171	21.3%
2	209029	60.2%
1	53705	15.5%

age
Real number (ℝ_≥0)

ZEROS

Distinct	42
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	26.53881353

Minimum	0
Maximum	995
Zeros	34725
Zeros (%)	10.0%
Negative	0
Negative (%)	0.0%
Memory size	2.7 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	10
median	15
Q3	30
95-th percentile	60
Maximum	995
Range	995
Interquartile range (IQR)	20

Descriptive statistics

Standard deviation	73.52774868
Coefficient of variation (CV)	2.770574072
Kurtosis	157.3751623
Mean	26.53881353
Median Absolute Deviation (MAD)	10
Skewness	12.19598992
Sum	9221415
Variance	5406.329825
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=42)

Value	Count	Frequency (%)
10	51680	14.9%
15	48074	13.8%
5	45045	13.0%
20	42792	12.3%
0	34725	10.0%
25	32586	9.4%
30	23977	6.9%
35	14420	4.2%
40	14050	4.0%
50	9619	2.8%
Other values (32)	30501	8.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	34725	10.0%
5	45045	13.0%
10	51680	14.9%
15	48074	13.8%
20	42792	12.3%
25	32586	9.4%
30	23977	6.9%
35	14420	4.2%
40	14050	4.0%
45	6255	1.8%

Value	Count	Frequency (%)
995	1851	0.5%
200	140	< 0.1%
195	2	< 0.1%
190	5	< 0.1%
185	1	< 0.1%
180	11	< 0.1%
175	5	< 0.1%
170	7	< 0.1%
165	2	< 0.1%
160	8	< 0.1%

area_percentage
Real number (ℝ_≥0)

Distinct	86
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	8.017014467

Minimum	1
Maximum	100
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.7 MiB

Quantile statistics

Minimum	1
5-th percentile	3
Q1	5
median	7
Q3	9
95-th percentile	16
Maximum	100
Range	99
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	4.388646483
Coefficient of variation (CV)	0.5474165602
Kurtosis	30.64344074
Mean	8.017014467
Median Absolute Deviation (MAD)	2
Skewness	3.53162645
Sum	2785664
Variance	19.26021795
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
6	55959	16.1%
7	49140	14.1%
5	43556	12.5%
8	37988	10.9%
9	29572	8.5%
4	25675	7.4%
10	21030	6.1%
11	18390	5.3%
3	15687	4.5%
12	10148	2.9%
Other values (76)	40324	11.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	125	< 0.1%
2	4275	1.2%
3	15687	4.5%
4	25675	7.4%
5	43556	12.5%
6	55959	16.1%
7	49140	14.1%
8	37988	10.9%
9	29572	8.5%
10	21030	6.1%

Value	Count	Frequency (%)
100	1	< 0.1%
96	3	< 0.1%
92	3	< 0.1%
90	1	< 0.1%
86	7	< 0.1%
85	5	< 0.1%
84	3	< 0.1%
83	4	< 0.1%
82	1	< 0.1%
81	1	< 0.1%

height_percentage
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	29
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.4347985

Minimum	2
Maximum	32
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.7 MiB

Quantile statistics

Minimum	2
5-th percentile	3
Q1	4
median	5
Q3	6
95-th percentile	9
Maximum	32
Range	30
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.915555029
Coefficient of variation (CV)	0.3524610948
Kurtosis	13.53489828
Mean	5.4347985
Median Absolute Deviation (MAD)	1
Skewness	1.762884329
Sum	1888424
Variance	3.669351069
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
5	104869	30.2%
6	61837	17.8%
4	50427	14.5%
7	47360	13.6%
3	34535	9.9%
8	18460	5.3%
2	12348	3.6%
9	7146	2.1%
10	5934	1.7%
12	1246	0.4%
Other values (19)	3307	1.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	12348	3.6%
3	34535	9.9%
4	50427	14.5%
5	104869	30.2%
6	61837	17.8%
7	47360	13.6%
8	18460	5.3%
9	7146	2.1%
10	5934	1.7%
11	1242	0.4%

Value	Count	Frequency (%)
32	90	< 0.1%
31	2	< 0.1%
29	1	< 0.1%
28	2	< 0.1%
26	3	< 0.1%
25	4	< 0.1%
24	6	< 0.1%
23	12	< 0.1%
22	3	< 0.1%
21	21	< 0.1%

land_surface_condition_1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

1	288937
0	58532

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	288937	83.2%
0	58532	16.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	288937	83.2%
0	58532	16.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

land_surface_condition_2
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	336350
1	11119

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	336350	96.8%
1	11119	3.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	336350	96.8%
1	11119	3.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

land_surface_condition_3
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	300056
1	47413

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	300056	86.4%
1	47413	13.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	300056	86.4%
1	47413	13.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

foundation_type
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

2.32957261993832	292374
1.810953829871676	20048
1.8836605890603086	18908
1.4533509783533416	14182
2.1056629834254146	1957

Length

Max length	18
Median length	16
Mean length	16.25942458
Min length	16

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.32957261993832
2nd row	2.32957261993832
3rd row	2.32957261993832
4th row	2.32957261993832
5th row	2.32957261993832

Common Values

Value	Count	Frequency (%)
2.32957261993832	292374	84.1%
1.810953829871676	20048	5.8%
1.8836605890603086	18908	5.4%
1.4533509783533416	14182	4.1%
2.1056629834254146	1957	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.32957261993832	292374	84.1%
1.810953829871676	20048	5.8%
1.8836605890603086	18908	5.4%
1.4533509783533416	14182	4.1%
2.1056629834254146	1957	0.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

roof_type_1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

1	243975
0	103494

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	243975	70.2%
0	103494	29.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	243975	70.2%
0	103494	29.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

roof_type_2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	265564
1	81905

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	265564	76.4%
1	81905	23.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	265564	76.4%
1	81905	23.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

roof_type_3
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	325880
1	21589

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	325880	93.8%
1	21589	6.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	325880	93.8%
1	21589	6.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

ground_floor_type
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

2.309103659496515	279591
2.25071351047152	33109
1.634204855040052	32731
2.0737051792828685	1334
1.970472440944882	704

Length

Max length	18
Median length	17
Mean length	16.90855299
Min length	16

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.309103659496515
2nd row	2.25071351047152
3rd row	2.309103659496515
4th row	2.309103659496515
5th row	2.309103659496515

Common Values

Value	Count	Frequency (%)
2.309103659496515	279591	80.5%
2.25071351047152	33109	9.5%
1.634204855040052	32731	9.4%
2.0737051792828685	1334	0.4%
1.970472440944882	704	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.309103659496515	279591	80.5%
2.25071351047152	33109	9.5%
1.634204855040052	32731	9.4%
2.0737051792828685	1334	0.4%
1.970472440944882	704	0.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

other_floor_type_1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

1	220286
0	127183

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
1	220286	63.4%
0	127183	36.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	220286	63.4%
0	127183	36.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

other_floor_type_2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	289330
1	58139

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
0	289330	83.3%
1	58139	16.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	289330	83.3%
1	58139	16.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

other_floor_type_3
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	294557
1	52912

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	294557	84.8%
1	52912	15.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	294557	84.8%
1	52912	15.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

other_floor_type_4
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	331337
1	16132

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	331337	95.4%
1	16132	4.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	331337	95.4%
1	16132	4.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

position_1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	290211
1	57258

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	290211	83.5%
1	57258	16.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	290211	83.5%
1	57258	16.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

position_2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

1	269463
0	78006

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	0
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	269463	77.6%
0	78006	22.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	269463	77.6%
0	78006	22.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

position_3
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	329822
1	17647

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	329822	94.9%
1	17647	5.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	329822	94.9%
1	17647	5.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

position_4
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	344368
1	3101

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	344368	99.1%
1	3101	0.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	344368	99.1%
1	3101	0.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

plan_configuration
Real number (ℝ_≥0)

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.238217454

Minimum	1.836923077
Maximum	2.272727273
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.7 MiB

Quantile statistics

Minimum	1.836923077
5-th percentile	2.24364583
Q1	2.24364583
median	2.24364583
Q3	2.24364583
95-th percentile	2.24364583
Maximum	2.272727273
Range	0.4358041958
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.04462032701
Coefficient of variation (CV)	0.01993565322
Kurtosis	51.37833059
Mean	2.238217454
Median Absolute Deviation (MAD)	0
Skewness	-7.219765384
Sum	777711.1806
Variance	0.001990973582
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
2.24364583	333327	95.9%
2.271433591	7641	2.2%
1.91833379	4909	1.4%
1.836923077	450	0.1%
2.049132948	449	0.1%
1.853174603	353	0.1%
1.893081761	195	0.1%
1.913043478	64	< 0.1%
2.157894737	54	< 0.1%
2.272727273	27	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1.836923077	450	0.1%
1.853174603	353	0.1%
1.893081761	195	0.1%
1.913043478	64	< 0.1%
1.91833379	4909	1.4%
2.049132948	449	0.1%
2.157894737	54	< 0.1%
2.24364583	333327	95.9%
2.271433591	7641	2.2%
2.272727273	27	< 0.1%

Value	Count	Frequency (%)
2.272727273	27	< 0.1%
2.271433591	7641	2.2%
2.24364583	333327	95.9%
2.157894737	54	< 0.1%
2.049132948	449	0.1%
1.91833379	4909	1.4%
1.913043478	64	< 0.1%
1.893081761	195	0.1%
1.853174603	353	0.1%
1.836923077	450	0.1%

has_superstructure_adobe_mud
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	316554
1	30915

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	316554	91.1%
1	30915	8.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	316554	91.1%
1	30915	8.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_mud_mortar_stone
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

1	264798
0	82671

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
1	264798	76.2%
0	82671	23.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	264798	76.2%
0	82671	23.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_stone_flag
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	335528
1	11941

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	335528	96.6%
1	11941	3.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	335528	96.6%
1	11941	3.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_cement_mortar_stone
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	341104
1	6365

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	341104	98.2%
1	6365	1.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	341104	98.2%
1	6365	1.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_mud_mortar_brick
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	323848
1	23621

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	323848	93.2%
1	23621	6.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	323848	93.2%
1	23621	6.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_cement_mortar_brick
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	321440
1	26029

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	321440	92.5%
1	26029	7.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	321440	92.5%
1	26029	7.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_timber
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	258995
1	88474

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	258995	74.5%
1	88474	25.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	258995	74.5%
1	88474	25.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_bamboo
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	318046
1	29423

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	318046	91.5%
1	29423	8.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	318046	91.5%
1	29423	8.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_rc_non_engineered
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	332678
1	14791

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	332678	95.7%
1	14791	4.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	332678	95.7%
1	14791	4.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_rc_engineered
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	341964
1	5505

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	341964	98.4%
1	5505	1.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	341964	98.4%
1	5505	1.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_superstructure_other
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	342243
1	5226

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	342243	98.5%
1	5226	1.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	342243	98.5%
1	5226	1.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

legal_ownership_status
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

2.2440632982517665	334633
1.8940493468795356	7307
2.4157639148300336	3539
2.2172437202987103	1990

Length

Max length	18
Median length	18
Mean length	18
Min length	18

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.2440632982517665
2nd row	2.2440632982517665
3rd row	2.2440632982517665
4th row	2.2440632982517665
5th row	2.2440632982517665

Common Values

Value	Count	Frequency (%)
2.2440632982517665	334633	96.3%
1.8940493468795356	7307	2.1%
2.4157639148300336	3539	1.0%
2.2172437202987103	1990	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.2440632982517665	334633	96.3%
1.8940493468795356	7307	2.1%
2.4157639148300336	3539	1.0%
2.2172437202987103	1990	0.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

count_families
Real number (ℝ_≥0)

ZEROS

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.9837395566

Minimum	0
Maximum	9
Zeros	27937
Zeros (%)	8.0%
Negative	0
Negative (%)	0.0%
Memory size	2.7 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	1
Q3	1
95-th percentile	2
Maximum	9
Range	9
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.4193854935
Coefficient of variation (CV)	0.4263176069
Kurtosis	17.24872251
Mean	0.9837395566
Median Absolute Deviation (MAD)	0
Skewness	1.627559333
Sum	341819
Variance	0.1758841922
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1	301377	86.7%
0	27937	8.0%
2	15010	4.3%
3	2415	0.7%
4	547	0.2%
5	135	< 0.1%
6	33	< 0.1%
7	8	< 0.1%
9	4	< 0.1%
8	3	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	27937	8.0%
1	301377	86.7%
2	15010	4.3%
3	2415	0.7%
4	547	0.2%
5	135	< 0.1%
6	33	< 0.1%
7	8	< 0.1%
8	3	< 0.1%
9	4	< 0.1%

Value	Count	Frequency (%)
9	4	< 0.1%
8	3	< 0.1%
7	8	< 0.1%
6	33	< 0.1%
5	135	< 0.1%
4	547	0.2%
3	2415	0.7%
2	15010	4.3%
1	301377	86.7%
0	27937	8.0%

has_secondary_use
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	308630
1	38839

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	308630	88.8%
1	38839	11.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	308630	88.8%
1	38839	11.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_agriculture
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	325124
1	22345

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	325124	93.6%
1	22345	6.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	325124	93.6%
1	22345	6.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_hotel
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	335764
1	11705

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	335764	96.6%
1	11705	3.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	335764	96.6%
1	11705	3.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_rental
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	344642
1	2827

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	344642	99.2%
1	2827	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	344642	99.2%
1	2827	0.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_institution
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	347136
1	333

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	347136	99.9%
1	333	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	347136	99.9%
1	333	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_school
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	347343
1	126

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	347343	> 99.9%
1	126	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	347343	> 99.9%
1	126	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_industry
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	347103
1	366

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	347103	99.9%
1	366	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	347103	99.9%
1	366	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_health_post
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	347411
1	58

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	347411	> 99.9%
1	58	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	347411	> 99.9%
1	58	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_gov_office
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	347421
1	48

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	347421	> 99.9%
1	48	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	347421	> 99.9%
1	48	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_use_police
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	347442
1	27

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	347442	> 99.9%
1	27	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	347442	> 99.9%
1	27	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

has_secondary_use_other
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.7 MiB

0	345709
1	1760

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	345709	99.5%
1	1760	0.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	345709	99.5%
1	1760	0.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	building_id	geo_level_1_id	geo_level_2_id	geo_level_3_id	count_floors_pre_eq	age	area_percentage	height_percentage	land_surface_condition_1	land_surface_condition_2	land_surface_condition_3	foundation_type	roof_type_1	roof_type_2	ground_floor_type	other_floor_type_1	other_floor_type_2	other_floor_type_3	position_1	position_2	plan_configuration	has_superstructure_adobe_mud	has_superstructure_mud_mortar_stone	has_superstructure_cement_mortar_brick	has_superstructure_timber	has_superstructure_bamboo	legal_ownership_status	count_families	has_secondary_use	has_secondary_use_agriculture
0	802906	2.161724	2.740741	2.837838	2	30	6	5	1	0	0	2.329573	1	0	2.309104	1	0	0	1	0	2.243646	1	1	0	0	0	2.244063	1	0	0
1	28830	2.485273	2.487437	2.062500	2	10	8	7	0	1	0	2.329573	1	0	2.250714	1	0	0	0	1	2.243646	0	1	0	0	0	2.244063	1	0	0
2	94947	2.563369	2.518750	2.580882	2	10	5	5	1	0	0	2.329573	1	0	2.309104	0	1	0	1	0	2.243646	0	1	0	0	0	2.244063	1	0	0
3	590882	2.000960	2.107317	2.096774	2	10	6	5	1	0	0	2.329573	1	0	2.309104	0	1	0	0	1	2.243646	0	1	0	1	1	2.244063	1	0	0
4	201944	2.337713	2.348748	2.368852	3	30	8	9	1	0	0	2.329573	1	0	2.309104	0	1	0	0	1	2.243646	1	0	0	0	0	2.244063	1	0	0
5	333020	2.485273	2.546539	2.368421	2	10	9	5	1	0	0	2.329573	1	0	2.309104	1	0	0	0	1	2.243646	0	1	0	0	0	2.244063	1	1	1
6	728451	2.026023	2.137681	2.555556	2	25	3	4	0	0	1	2.329573	1	0	2.250714	1	0	0	0	1	2.243646	0	1	0	0	0	2.244063	1	0	0
7	475515	1.926464	1.282869	1.100000	2	0	8	6	1	0	0	1.810954	0	1	1.634205	0	1	0	0	1	1.918334	0	0	1	1	0	2.244063	1	0	0
8	441126	2.065320	2.105085	2.189189	2	15	8	6	1	0	0	2.329573	0	1	2.309104	1	0	0	0	1	2.243646	0	1	0	1	0	2.244063	1	0	0
9	989500	1.730887	1.545109	1.551402	1	0	13	4	1	0	0	1.453351	1	0	1.634205	0	0	1	0	1	2.243646	0	0	1	0	0	2.244063	1	0	0

Last rows

	building_id	geo_level_1_id	geo_level_2_id	geo_level_3_id	count_floors_pre_eq	age	area_percentage	height_percentage	land_surface_condition_1	land_surface_condition_3	foundation_type	roof_type_1	roof_type_2	roof_type_3	ground_floor_type	other_floor_type_1	other_floor_type_2	other_floor_type_3	other_floor_type_4	position_1	position_2	plan_configuration	has_superstructure_adobe_mud	has_superstructure_mud_mortar_stone	has_superstructure_stone_flag	has_superstructure_cement_mortar_brick	has_superstructure_timber	has_superstructure_bamboo	has_superstructure_rc_non_engineered	has_superstructure_rc_engineered	legal_ownership_status	count_families	has_secondary_use	has_secondary_use_agriculture	has_secondary_use_hotel
347459	290842	2.794480	2.953908	3.000000	3	5	5	5	1	0	2.329573	1	0	0	2.309104	1	0	0	0	0	1	2.243646	0	1	0	0	1	1	0	0	2.244063	1	0	0	0
347460	330371	2.162136	2.216958	2.500000	2	25	9	5	1	0	2.329573	0	1	0	2.309104	1	0	0	0	0	1	2.243646	0	1	0	0	0	0	0	0	2.244063	1	0	0	0
347461	698612	1.926464	1.433054	1.523810	2	10	9	5	1	0	1.810954	0	1	0	2.309104	0	1	0	0	0	1	1.918334	0	0	0	0	1	0	0	0	2.244063	1	0	0	0
347462	445192	2.161724	1.991354	1.868852	2	5	14	6	1	0	2.329573	0	0	1	2.250714	0	0	0	1	0	1	2.243646	0	0	0	0	0	0	1	0	2.244063	1	0	0	0
347463	640115	2.297726	2.074919	2.071713	2	5	16	5	1	0	1.453351	0	0	1	1.634205	0	0	0	1	0	1	2.243646	0	0	0	0	0	0	0	1	2.244063	2	1	0	1
347464	310028	2.162136	2.122642	1.861111	3	70	20	6	1	0	2.329573	0	1	0	2.309104	1	0	0	0	1	0	2.243646	0	1	0	0	1	0	0	0	2.415764	1	1	1	0
347465	663567	2.341954	2.337176	2.722222	3	25	6	7	0	1	2.329573	1	0	0	2.309104	1	0	0	0	0	1	2.243646	1	1	1	0	0	0	0	0	2.244063	1	0	0	0
347466	1049160	2.000960	2.019704	1.909091	1	50	3	3	1	0	2.329573	1	0	0	2.309104	0	0	1	0	0	1	2.243646	0	1	0	0	1	0	0	0	2.244063	1	0	0	0
347467	442785	2.161724	2.295950	2.136364	2	5	9	5	1	0	2.329573	1	0	0	2.309104	1	0	0	0	0	1	2.243646	1	1	0	0	0	0	0	0	1.894049	1	0	0	0
347468	501372	1.730887	1.433918	1.514286	2	10	11	4	1	0	2.329573	0	1	0	1.634205	1	0	0	0	0	1	2.243646	0	0	0	1	0	0	0	0	2.244063	1	0	0	0

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script